5 papers
Lightweight Embedded FPGA Deployment of Learned Image Compression with Knowledge Distillation and Hybrid Quantization
Alaa Mazouz, Sumanta Chaudhuri, Marco Cagnanzzo +3
Learnable Image Compression (LIC) has shown the potential to outperform standardized video codecs in RD efficiency, prompting the research for hardware-friendly implementations. Mo…
Security and Real-time FPGA integration for Learned Image Compression
Alaa Mazouz, Carl De Sousa Tria, Sumanta Chaudhuri +4
Learnable Image Compression (LIC) has proven capable of outperforming standardized video codecs in compression efficiency. However, achieving both real-time and secure LIC operatio…
Compression in 3D Gaussian Splatting: A Survey of Methods, Trends, and Future Directions
Muhammad Salman Ali, Chaoning Zhang, Marco Cagnazzo +3
3D Gaussian Splatting (3DGS) has recently emerged as a pioneering approach in explicit scene rendering and computer graphics. Unlike traditional neural radiance field (NeRF) method…
WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking
Carl De Sousa Trias, Mihai Mitrea, Attilio Fiandrotti +3
Nowadays, deep neural networks are used for solving complex tasks in several critical applications and protecting both their integrity and intellectual property rights (IPR) has be…
Find the Lady: Permutation and Re-Synchronization of Deep Neural Networks
Carl De Sousa Trias, Mihai Petru Mitrea, Attilio Fiandrotti +3
Deep neural networks are characterized by multiple symmetrical, equi-loss solutions that are redundant. Thus, the order of neurons in a layer and feature maps can be given arbitrar…